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I' ?I/;I4"I:=II I !I' c [S5S[S[S[S[S[ S0n[ [[[[[S5S.n[ URUS5URUS55nX4$)Nrrrr)rxrwrrrr)r0rrrrr1rErh)type1type2typesinvtypes moregenerics r _more_genericr~sw T A a Q q q Q  E      : Heiiq)599UA+>?K   rcnUVs/sHn[X1U5PM nn[[U[5$s snf)uThe least generic type all column values are convertible to. >>> _column_type([True, False]) is bool True >>> _column_type(["1", "2"]) is int True >>> _column_type(["1", "2.3"]) is float True >>> _column_type(["1", "2.3", "four"]) is str True >>> _column_type(["four", 'пять']) is str True >>> _column_type([None, "brux"]) is str True >>> _column_type([1, 2, None]) is int True >>> import datetime as dt >>> _column_type([dt.datetime(1991,2,19), dt.time(17,35)]) is str True )rr r~r)rWrrr'r{s r _column_typers5,9@ @1U1X .E @ - -- As2cUcU$[U[[45(aU(dgU[LaU$U[La[U[5(aUR S5R S5n[ R"SU5nU(a[UR55nUS:XaURS5n U R5(aYURS5[[U 5U5-URS5-n U R S5R S5nSn[X5$U[La [US5$U[LaU=(a [U[[45n U (a2[!U5n [[U 5U5n UR%X5$[U[5(aS U;aUR%S S5n[[U5U5$U$![[4a [U5s$f=f!["[4a Us$f=f!["[4a Us$f=f) uFormat a value according to its deduced type. 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Unicode is supported: >>> hrow = ['буква', 'цифра'] ; tbl = [['аз', 2], ['буки', 4]] ; good_result = '\u0431\u0443\u043a\u0432\u0430 \u0446\u0438\u0444\u0440\u0430\n------- -------\n\u0430\u0437 2\n\u0431\u0443\u043a\u0438 4' ; tabulate(tbl, headers=hrow) == good_result True runicode_escapezutf-8z/(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$rrrasciir)rrr1rencoderrr>r8groupsgroupisdigitr~rrrrrreplace)rvaltypefloatfmtintfmt missingvalr val_stripedcolored total_groupsdigitsval_newis_a_colored_numberraw_val formatted_vals r_formatr-s {#s|$$S#~ C c3  **%56==gFKiiBKG"7>>#34 1$$]]1-F~~''#MM!,$S[&9:%mmA./ &nnW5<<=MNFc"" E  sG$ $ E +M 3e 0M !#&G &uW~x @ ;;w6 6#s##s kk#r* eCj(33'-. s8O  *   *  s6 G9 H!H39HHH0/H03I I c HU(aN[R"[U5nUVs/sHn[XqX%"U55PM nnSR U5$[ U5U- n X)- nUS:Xa [ X 5$US:Xa [X 5$U(dU$[X 5$s snf)zIPad string header to width chars given known visible_width of the header.rrCrB) rrFr? _align_headerrTr8r,r.r)) rrlr^ visible_widthrSrT header_linesh padded_lines ninvisibles rrrlsxx 0&9 EQ EQM!x{ ;\  yy&&V},J EF'' h && && sBc[U[5(aO/n/n[U5H9up4[U5(aUR U5 M(UR U5 M; X!4$US4$r)rr7 enumerater<r)rseparating_lines sans_rowsindexr9s r_remove_separating_linesrsf$ #D/JE"3'' ''.  % * **TzrcRU(a UHnURU[5 M ggr)insertr3)rrrs r_reinsert_separating_linesrs"%E KK /&rc rUbUSLaU$[U[5(a>[U5[U5:wa&[SS[U5S[U53-5e[ U5up#/n[ U5nUH,n[ U5nURU/[U5-5 M. Un[X5 U$)zAdd a left-most index column.Fz2index must be as long as the number of data rows: z len(index)=z len(rows)=) rr r8rriternextrr7r)rrrrr index_iterr9index_vs r_prepend_row_indexrs } %CJ#d)$; @CJ<{3t9+> ?  #;4"@IHeJz" DI-. Dt6 Krc:[U5$![a gf=f)zDA wrapper around standard bool() which doesn't throw on NumPy arraysF)rrrs r_boolrs#Cy s c X[U5 SnSn[US5(Ga\[US5(GaJ[ UR 5(a1UR 5n[[UR 565nO[US5(a[U5nUS;atURRb][URR[5(aURRUSS&OURR/USS&UR n[UR5nUVs/sHn[U5PM nnO [S5eUS:Xa[[[U55nGO[U5nUS:Xa U(d/nGOUS:XaD[US 5(a3URR(aURRnGOUS:Xac[!U5S:aT[US["5(a<[USS 5(a([[[USR$55nGO[!U5S:Ga[USS5(Ga[USS5(Ga['5n /nUS :XaK[!U5S:aUSO0n UR)U R 55 U R+U5 US SnUHCnUR 5H,n X;dM UR-U 5 U R/U 5 M. ME US:XaUnO[U[05(a:UV s/sHoR3X5PM nn [[[U55nOeUS :XaM[!U5S:a;UV s/sHn W R3X5PM nn [[[U55nO/nOU(a [S 5eUVV s/sH#oV s/sHoR3U 5PM sn PM% nnn GOJUS:XaR[US5(aA[US5(a0[US5(aUR4V s/sHoSPM nn O[6b[!U5S:a[6R8"US5(a{[6R:"US5V s/sHoRPM nn US:XaUnUVVs/sH1n[=U5(dUVs/sHn[?X5PM snOUPM3 nnnOCUS:Xa=[!U5S:a.[[[[A[!US5555nUS :XaQ[!U5S:aBUbUS/[US5-nUS SnOUSn[[[U55nUS SnOUS :Xa/n[[[U55n[[SU55n[CU5[[D4;nUS:XaUb [GXd5nO[U[H5(aU(d[GU[U55nO[U[J5(aU(d [GXb5nOgUS:Xd[MU5(a3U(d,Uc[[A[!U555n[GXd5nOUS:Xd[MU5(dU(dSnU(a<[!U5S:a-[OS[!US5[!U5- 5nS/U-U-nXaU4$![a [U5nGN:f=f![a [U5ef=fs snf![a [U5ef=fs sn fs sn fs sn fs sn nfs sn fs sn fs snfs snnf)aTransform a supported data type to a list of lists, and a list of headers, with headers padding. Supported tabular data types: * list-of-lists or another iterable of iterables * list of named tuples (usually used with headers="keys") * list of dicts (usually used with headers="keys") * list of OrderedDicts (usually used with headers="keys") * list of dataclasses (usually used with headers="keys") * 2D NumPy arrays * NumPy record arrays (usually used with headers="keys") * dict of iterables (usually used with headers="keys") * pandas.DataFrame (usually used with headers="keys") The first row can be used as headers if headers="firstrow", column indices can be used as headers if headers="keys". If showindex="default", show row indices of the pandas.DataFrame. If showindex="always", show row indices for all types of data. If showindex="never", don't show row indices for all types of data. If showindex is an iterable, show its values as row indices. z To build a table python-tabulate requires two-dimensional data like a list of lists or similar. Did you forget a pair of extra [] or ',' in ()?Nkeysrvr)ralwaysTrz7tabular data doesn't appear to be a dict or a DataFramedtype_fieldsfirstrowrz6headers for a list of dicts is not a dict or a keyword descriptionfetchonerowcountc<[U5(aU$[U5$r)r<r7)rs rrN)_normalize_tabular_data..hs#6q#9#9aFtAwFrrrneverr)(rrr7rcallablervr izip_longestrrnamerrr1rnamesr8tuplersetreupdateradddictrhr dataclasses is_dataclassfieldsr<getattrranger0rrr rrrE) tabular_datar showindexerr_msgrrrvalsr9 uniq_keys firstdictkcolumnfield field_namesrshowindex_is_a_str headers_pads r_normalize_tabular_datarsD  W  < E|V$$x)H)H L'' ( ($$&D ) ,"5"5"78 \7 + + %D88 &&++7l0055t<<+1166D!H , 2 2 7 78D!H&&D++,E)-.#DID.DVW W f 3sD>*G % %D f TG v  g..""((#((..G v D A 47E**Q++3sDGOO45G Y]wtAw77GDGX>> repr(_to_str(b'foo')) "'foo'" >>> repr(_to_str('foo')) "'foo'" >>> repr(_to_str(42)) "'42'" )encodingerrors)rrrr1)r'rrs r_to_strrs+(!Uxxx99 q6MrrDcD^9Uc/n[XUS9unnn[U5unnU b[U 5[La [ U 5n [ U5(a[ US5nOSn[ U [5(a[U UU 5n O [U US5n [U U5n[UU UUUUS9nUbnU(a[ US5O [ U5n[ U[5(a[UUU5nO [UUS5n[U U5n[U/UUUUUS9SnUS:Xa[UU5unn[nUS:Xa!SnSn U[:XaSOUnU[:XaSOUnOU[:XaS OUnU[:XaS OUnUS :XaS n S nS R[[!["U5[R$"S U5555n[&R)U5SLn[*SL=(a [,n[ U[.5(d2U[0;a([3U5(a[0R5X"5nSnOSn[7UUU5m9[ [9U65n[U [ U55n[;UU5VV s/sHunn [=UU S9PM n!nn [ U[>5(a[ U5U/-n"OQ[ U5n"[ U"5[ U5:a.U"RA[ U5[ U"5- [B/-5 [ U[>5(a[ U5U/-n#OQ[ U5n#[ U#5[ U5:a.U#RA[ U5[ U#5- [D/-5 [ U[>5(a[ U5U/-n$OQ[ U5n$[ U$5[ U5:a.U$RA[ U5[ U$5- [F/-5 [;UU!U"U#U$5V%V&V'V(V)V*s/sH*un%n&n'n(n)U%V*s/sHn*[IU*U&U'U(U)U5PM sn*PM, nn)n(n'n&n%n*U bU /[ U5-n+O$U!V&s/sHn&U&[[J4;aUOUPM n+n&U b[ U [L5(de[ U [>5(a0[NRP"SU V%s/sHn%U%PM sn%SU SU S3SS9 [SU 5H$un,n-U,[ U+5:d OU-S:wdMU-U+U,'M& U(aUV.s/sHn.T9"U.5U-PM sn.OS/[ U5-n/U+RU5n0US :XaS /[ U5-n0[;UU0U/5V%V1V2s/sHun%n1n2[WU%U1U2UUUU 5PM nn1n%n2Sn3U(GaU=(d S//[ U5-n4UbU/[ U45-n3OU+=(d U/[ U5-n3Ub[ U[L5(de[ U[>5(a0[NRP"SUV%s/sHn%U%PM sn%SUSUS3SS9 [SU5HHun,n-UU,-n5U5[ U35:d O0U-S:XaU5[ U+5:a U+U5U3U5'M;U-S:wdMCU-U3U5'MJ [;U/U45V2V%s/sH%un2n%[YU2[YU94SjU%555PM' n/n2n%[;UU3U/5V.V1V2s/sHun.n1n2[[U.U1U2T9"U.5UT95PM nn1n.n2[ [;U65n6O6UV%s/sHn%[YU94SjU%55PM n/n%[ [;U65n6[ U[.5(d[\R5U[\S5n[ U[>5(aUOSn7[U[ U65U75n8[_U6U5 [aUUU3U6U/U+UU8S9$s sn nfs sn*fs sn*n)n(n'n&n%fs sn&fs sn%fs sn.fs sn2n1n%fs sn%fs sn%n2fs sn2n1n.fs sn%f) uKFormat a fixed width table for pretty printing. >>> print(tabulate([[1, 2.34], [-56, "8.999"], ["2", "10001"]])) --- --------- 1 2.34 -56 8.999 2 10001 --- --------- The first required argument (`tabular_data`) can be a list-of-lists (or another iterable of iterables), a list of named tuples, a dictionary of iterables, an iterable of dictionaries, an iterable of dataclasses, a two-dimensional NumPy array, NumPy record array, or a Pandas' dataframe. Table headers ------------- To print nice column headers, supply the second argument (`headers`): - `headers` can be an explicit list of column headers - if `headers="firstrow"`, then the first row of data is used - if `headers="keys"`, then dictionary keys or column indices are used Otherwise a headerless table is produced. If the number of headers is less than the number of columns, they are supposed to be names of the last columns. This is consistent with the plain-text format of R and Pandas' dataframes. >>> print(tabulate([["sex","age"],["Alice","F",24],["Bob","M",19]], ... headers="firstrow")) sex age ----- ----- ----- Alice F 24 Bob M 19 By default, pandas.DataFrame data have an additional column called row index. To add a similar column to all other types of data, use `showindex="always"` or `showindex=True`. To suppress row indices for all types of data, pass `showindex="never" or `showindex=False`. To add a custom row index column, pass `showindex=some_iterable`. >>> print(tabulate([["F",24],["M",19]], showindex="always")) - - -- 0 F 24 1 M 19 - - -- Column and Headers alignment ---------------------------- `tabulate` tries to detect column types automatically, and aligns the values properly. By default it aligns decimal points of the numbers (or flushes integer numbers to the right), and flushes everything else to the left. Possible column alignments (`numalign`, `stralign`) are: "right", "center", "left", "decimal" (only for `numalign`), and None (to disable alignment). `colglobalalign` allows for global alignment of columns, before any specific override from `colalign`. Possible values are: None (defaults according to coltype), "right", "center", "decimal", "left". `colalign` allows for column-wise override starting from left-most column. Possible values are: "global" (no override), "right", "center", "decimal", "left". `headersglobalalign` allows for global headers alignment, before any specific override from `headersalign`. Possible values are: None (follow columns alignment), "right", "center", "left". `headersalign` allows for header-wise override starting from left-most given header. Possible values are: "global" (no override), "same" (follow column alignment), "right", "center", "left". Note on intended behaviour: If there is no `tabular_data`, any column alignment argument is ignored. Hence, in this case, header alignment cannot be inferred from column alignment. Table formats ------------- `intfmt` is a format specification used for columns which contain numeric data without a decimal point. This can also be a list or tuple of format strings, one per column. `floatfmt` is a format specification used for columns which contain numeric data with a decimal point. This can also be a list or tuple of format strings, one per column. `None` values are replaced with a `missingval` string (like `floatfmt`, this can also be a list of values for different columns): >>> print(tabulate([["spam", 1, None], ... ["eggs", 42, 3.14], ... ["other", None, 2.7]], missingval="?")) ----- -- ---- spam 1 ? eggs 42 3.14 other ? 2.7 ----- -- ---- Various plain-text table formats (`tablefmt`) are supported: 'plain', 'simple', 'grid', 'pipe', 'orgtbl', 'rst', 'mediawiki', 'latex', 'latex_raw', 'latex_booktabs', 'latex_longtable' and tsv. Variable `tabulate_formats`contains the list of currently supported formats. "plain" format doesn't use any pseudographics to draw tables, it separates columns with a double space: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "plain")) strings numbers spam 41.9999 eggs 451 >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="plain")) spam 41.9999 eggs 451 "simple" format is like Pandoc simple_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "simple")) strings numbers --------- --------- spam 41.9999 eggs 451 >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="simple")) ---- -------- spam 41.9999 eggs 451 ---- -------- "grid" is similar to tables produced by Emacs table.el package or Pandoc grid_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "grid")) +-----------+-----------+ | strings | numbers | +===========+===========+ | spam | 41.9999 | +-----------+-----------+ | eggs | 451 | +-----------+-----------+ >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="grid")) +------+----------+ | spam | 41.9999 | +------+----------+ | eggs | 451 | +------+----------+ "simple_grid" draws a grid using single-line box-drawing characters: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "simple_grid")) ┌───────────┬───────────┐ │ strings │ numbers │ ├───────────┼───────────┤ │ spam │ 41.9999 │ ├───────────┼───────────┤ │ eggs │ 451 │ └───────────┴───────────┘ "rounded_grid" draws a grid using single-line box-drawing characters with rounded corners: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "rounded_grid")) ╭───────────┬───────────╮ │ strings │ numbers │ ├───────────┼───────────┤ │ spam │ 41.9999 │ ├───────────┼───────────┤ │ eggs │ 451 │ ╰───────────┴───────────╯ "heavy_grid" draws a grid using bold (thick) single-line box-drawing characters: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "heavy_grid")) ┏━━━━━━━━━━━┳━━━━━━━━━━━┓ ┃ strings ┃ numbers ┃ ┣━━━━━━━━━━━╋━━━━━━━━━━━┫ ┃ spam ┃ 41.9999 ┃ ┣━━━━━━━━━━━╋━━━━━━━━━━━┫ ┃ eggs ┃ 451 ┃ ┗━━━━━━━━━━━┻━━━━━━━━━━━┛ "mixed_grid" draws a grid using a mix of light (thin) and heavy (thick) lines box-drawing characters: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "mixed_grid")) ┍━━━━━━━━━━━┯━━━━━━━━━━━┑ │ strings │ numbers │ ┝━━━━━━━━━━━┿━━━━━━━━━━━┥ │ spam │ 41.9999 │ ├───────────┼───────────┤ │ eggs │ 451 │ ┕━━━━━━━━━━━┷━━━━━━━━━━━┙ "double_grid" draws a grid using double-line box-drawing characters: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "double_grid")) ╔═══════════╦═══════════╗ ║ strings ║ numbers ║ ╠═══════════╬═══════════╣ ║ spam ║ 41.9999 ║ ╠═══════════╬═══════════╣ ║ eggs ║ 451 ║ ╚═══════════╩═══════════╝ "fancy_grid" draws a grid using a mix of single and double-line box-drawing characters: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "fancy_grid")) ╒═══════════╤═══════════╕ │ strings │ numbers │ ╞═══════════╪═══════════╡ │ spam │ 41.9999 │ ├───────────┼───────────┤ │ eggs │ 451 │ ╘═══════════╧═══════════╛ "colon_grid" is similar to "grid" but uses colons only to define columnwise content alignment, without whitespace padding, similar to the alignment specification of Pandoc `grid_tables`: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "colon_grid")) +-----------+-----------+ | strings | numbers | +:==========+:==========+ | spam | 41.9999 | +-----------+-----------+ | eggs | 451 | +-----------+-----------+ >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "colon_grid", ... colalign=["right", "left"])) +-----------+-----------+ | strings | numbers | +==========:+:==========+ | spam | 41.9999 | +-----------+-----------+ | eggs | 451 | +-----------+-----------+ "outline" is the same as the "grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "outline")) +-----------+-----------+ | strings | numbers | +===========+===========+ | spam | 41.9999 | | eggs | 451 | +-----------+-----------+ >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="outline")) +------+----------+ | spam | 41.9999 | | eggs | 451 | +------+----------+ "simple_outline" is the same as the "simple_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "simple_outline")) ┌───────────┬───────────┐ │ strings │ numbers │ ├───────────┼───────────┤ │ spam │ 41.9999 │ │ eggs │ 451 │ └───────────┴───────────┘ "rounded_outline" is the same as the "rounded_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "rounded_outline")) ╭───────────┬───────────╮ │ strings │ numbers │ ├───────────┼───────────┤ │ spam │ 41.9999 │ │ eggs │ 451 │ ╰───────────┴───────────╯ "heavy_outline" is the same as the "heavy_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "heavy_outline")) ┏━━━━━━━━━━━┳━━━━━━━━━━━┓ ┃ strings ┃ numbers ┃ ┣━━━━━━━━━━━╋━━━━━━━━━━━┫ ┃ spam ┃ 41.9999 ┃ ┃ eggs ┃ 451 ┃ ┗━━━━━━━━━━━┻━━━━━━━━━━━┛ "mixed_outline" is the same as the "mixed_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "mixed_outline")) ┍━━━━━━━━━━━┯━━━━━━━━━━━┑ │ strings │ numbers │ ┝━━━━━━━━━━━┿━━━━━━━━━━━┥ │ spam │ 41.9999 │ │ eggs │ 451 │ ┕━━━━━━━━━━━┷━━━━━━━━━━━┙ "double_outline" is the same as the "double_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "double_outline")) ╔═══════════╦═══════════╗ ║ strings ║ numbers ║ ╠═══════════╬═══════════╣ ║ spam ║ 41.9999 ║ ║ eggs ║ 451 ║ ╚═══════════╩═══════════╝ "fancy_outline" is the same as the "fancy_grid" format but doesn't draw lines between rows: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "fancy_outline")) ╒═══════════╤═══════════╕ │ strings │ numbers │ ╞═══════════╪═══════════╡ │ spam │ 41.9999 │ │ eggs │ 451 │ ╘═══════════╧═══════════╛ "pipe" is like tables in PHP Markdown Extra extension or Pandoc pipe_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "pipe")) | strings | numbers | |:----------|----------:| | spam | 41.9999 | | eggs | 451 | "presto" is like tables produce by the Presto CLI: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "presto")) strings | numbers -----------+----------- spam | 41.9999 eggs | 451 >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="pipe")) |:-----|---------:| | spam | 41.9999 | | eggs | 451 | "orgtbl" is like tables in Emacs org-mode and orgtbl-mode. They are slightly different from "pipe" format by not using colons to define column alignment, and using a "+" sign to indicate line intersections: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "orgtbl")) | strings | numbers | |-----------+-----------| | spam | 41.9999 | | eggs | 451 | >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="orgtbl")) | spam | 41.9999 | | eggs | 451 | "rst" is like a simple table format from reStructuredText; please note that reStructuredText accepts also "grid" tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "rst")) ========= ========= strings numbers ========= ========= spam 41.9999 eggs 451 ========= ========= >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="rst")) ==== ======== spam 41.9999 eggs 451 ==== ======== "mediawiki" produces a table markup used in Wikipedia and on other MediaWiki-based sites: >>> print(tabulate([["strings", "numbers"], ["spam", 41.9999], ["eggs", "451.0"]], ... headers="firstrow", tablefmt="mediawiki")) {| class="wikitable" style="text-align: left;" |+ |- ! strings !! style="text-align: right;"| numbers |- | spam || style="text-align: right;"| 41.9999 |- | eggs || style="text-align: right;"| 451 |} "html" produces HTML markup as an html.escape'd str with a ._repr_html_ method so that Jupyter Lab and Notebook display the HTML and a .str property so that the raw HTML remains accessible the unsafehtml table format can be used if an unescaped HTML format is required: >>> print(tabulate([["strings", "numbers"], ["spam", 41.9999], ["eggs", "451.0"]], ... headers="firstrow", tablefmt="html"))
strings numbers
spam 41.9999
eggs 451
"latex" produces a tabular environment of LaTeX document markup: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="latex")) \begin{tabular}{lr} \hline spam & 41.9999 \\ eggs & 451 \\ \hline \end{tabular} "latex_raw" is similar to "latex", but doesn't escape special characters, such as backslash and underscore, so LaTeX commands may embedded into cells' values: >>> print(tabulate([["spam$_9$", 41.9999], ["\\emph{eggs}", "451.0"]], tablefmt="latex_raw")) \begin{tabular}{lr} \hline spam$_9$ & 41.9999 \\ \emph{eggs} & 451 \\ \hline \end{tabular} "latex_booktabs" produces a tabular environment of LaTeX document markup using the booktabs.sty package: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="latex_booktabs")) \begin{tabular}{lr} \toprule spam & 41.9999 \\ eggs & 451 \\ \bottomrule \end{tabular} "latex_longtable" produces a tabular environment that can stretch along multiple pages, using the longtable package for LaTeX. >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="latex_longtable")) \begin{longtable}{lr} \hline spam & 41.9999 \\ eggs & 451 \\ \hline \end{longtable} Number parsing -------------- By default, anything which can be parsed as a number is a number. This ensures numbers represented as strings are aligned properly. This can lead to weird results for particular strings such as specific git SHAs e.g. "42992e1" will be parsed into the number 429920 and aligned as such. To completely disable number parsing (and alignment), use `disable_numparse=True`. For more fine grained control, a list column indices is used to disable number parsing only on those columns e.g. `disable_numparse=[0, 2]` would disable number parsing only on the first and third columns. Column Widths and Auto Line Wrapping ------------------------------------ Tabulate will, by default, set the width of each column to the length of the longest element in that column. However, in situations where fields are expected to reasonably be too long to look good as a single line, tabulate can help automate word wrapping long fields for you. Use the parameter `maxcolwidths` to provide a list of maximal column widths: >>> print(tabulate( [('1', 'John Smith', 'This is a rather long description that might look better if it is wrapped a bit')], headers=("Issue Id", "Author", "Description"), maxcolwidths=[None, None, 30], tablefmt="grid" )) +------------+------------+-------------------------------+ | Issue Id | Author | Description | +============+============+===============================+ | 1 | John Smith | This is a rather long | | | | description that might look | | | | better if it is wrapped a bit | +------------+------------+-------------------------------+ Header column width can be specified in a similar way using `maxheadercolwidths`. N)rr)rrrrrrTrBr?rCrrc3B# UHn[[U5v M g7fr)rr)rMr9s rrOtabulate..E sK]cGS 1 1]sF)rz*As a string, `colalign` is interpreted as z". Did you mean `colglobalalign = "z"` or `colalign = ("z",)`?r) stacklevelglobalrz.As a string, `headersalign` is interpreted as z&. Did you mean `headersglobalalign = "z"` or `headersalign = ("samec34># UH nT"U5v M g7frrDrMclrTs rrOr s32(2,,c34># UH nT"U5v M g7frrDrs rrOr s2""rr) rowaligns)1rrr0rr7r8rrr_expand_numparserr MIN_PADDING_DEFAULT_ALIGNrTr rr from_iterabler3r>r8r9r&multiline_formatsrArhrUrrUrr1re_DEFAULT_FLOATFMT_DEFAULT_INTFMT_DEFAULT_MISSINGVALrrrwarningswarnrcopyrurEr_table_formatsr _format_table):rrtablefmtrrnumalignstralignrrdisable_numparsecolglobalalignrrX maxcolwidthsheadersglobalalign headersalignrowalignmaxheadercolwidthsrrrrrrr min_padding plain_textrrRrScolscolnpcoltypes float_formats int_formats missing_valsrmctfl_fmtint_fmtmiss_vrtalignsidxrEr minwidths aligns_copyrNminwaligns_headerst_colshidxr ra_defaultrrTs: @rrrsez *A+'M7K'?}&M#M#   & -L }  =+,HH lC ( (+L(LQL+L(DIL$%5x@ /  !--  %,93}Q'(s7| (# . .!1"H.@" "22DhPT!U $%5x@ ) I !--    5!9-!Q w K8 '>98x'>98x (N :9%76X <#  !   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If `original` is not a list to begin with (i.e. scalar value) a list of length `num_desired` completely populated with `default will be returned )rrr1r8)original num_desiredrs rrr sC(H%%j3.G.G){S]'BCCCy;&&rczU(a.U[:Xa[$SU-nUVs/sH o2U-U-PM nnU$U$s snf)Nrg)r3)cellsr-padr padded_cellss r_pad_rowr* sG O #" "Gm5:;UTd S(U ; +AKB S+& 'F00EB A80;@-H-QK0KbqEK0-KHR% %I&I L!5B1Hs(C CC C!C C!C!cU(dg[U5(aU"X5$Uup4pVUVs/sHotU-PM nn[XXV45$s snf)z3Return a string which represents a horizontal line.Nr-) rWrXlinefmtr!fillr#r$rGr's r _build_linerJ? sS y,, 'S#,-9a9- (9::.sAc<UR[XU55 U$r)rrJ)r0rWrXrHs r _append_linerLK s LLY7;< Lrc.\rSrSrSrSr\S5rSrg)JupyterHTMLStriP zQWrap the string with a _repr_html_ method so that Jupyter displays the HTML tablecU$rrDselfs r _repr_html_JupyterHTMLStr._repr_html_T s rcU$)z>add a .str property so that the raw string is still accessiblerDrPs rr1JupyterHTMLStr.strW s  rrDN) __name__ __module__ __qualname____firstlineno____doc__rRpropertyr1__static_attributes__rDrrrNrNP s rrNc ./nU(aUR(a URO/n URn URn UV s/sH oSU --PM n n U(aSn[[U S9nO [ n[ nU"X5nUR(aSU ;a[XXPR5 U(a8U"UUXU 5 UR(aSU ;a[XXPR5 U(aUR(a~SU ;ax[USSU5HBunnU[:waU"UU"UU 5U UURUS 9 [XXPR5 MD U"UU"USU 5U UURUSS 9 OUR=(dG UR=(d4 UR=(d! UR=(d [S S S S 5nUH=n[!U5(a[XUU5 M"U"X"UU 5XUR5 M? UR(aS U ;a[XXPR5 U(dU(a2S R#U5nUR[$:Xa ['U5$U$g s sn f) z1Produce a plain-text representation of the table.rcU$rrD)r9rs rrN_format_table..i s3r)r(r'r(r)Nr)r rr*r)r.r-r+rrFr*r1r'rLr(r)rUr3r,r*r r<rTr{rN)r(r headersalignsrrWrXrSrr0hiddenr(r+rGr?pad_row append_rowpadded_headersr9ralignseparating_lineoutputs rrr] sI E&-#2F2FS ! !RF ++C I,56Iq!c'kIM6  2< & W*N }}F2U9mmD5.- R   #4F#B y:M:M N ##(9(GtCRy)4KCo%C%!KK#  y:M:M N5   DHc "   KKr]      $"" $}} $}} $BB# C#3''U9oN73,m   }}F2U9mmD$5! ==< <!&) )MM7sJc@\rSrSrSrSr\S5rSrSr Sr Sr g ) ri aGA custom implementation of CPython's textwrap.TextWrapper. This supports both wide characters (Korea, Japanese, Chinese) - including mixed string. For the most part, the `_handle_long_word` and `_wrap_chunks` functions were copy pasted out of the CPython baseline, and updated with our custom length and line appending logic. ch/UlSUl[RR"U/UQ70UD6 gr) _active_codes max_linestextwrap TextWrapper__init__)rQrkwargss rrn_CustomTextWrap.__init__ s/%%dfindallr$rpop)rQreversed_chunkscur_linecur_lenr^ space_leftchunkrBstripped_chunktotal_escape_len last_grouprr escape_lenfounds r_handle_long_word!_CustomTextWrap._handle_long_word s 19JJ  Z!^$B'EA(/NS((TYY~bq7I-Jj-XES((TYY~bq7I-Jj-X ! J!!%(4&1&9&9%&@NE1a!$UJ a.BZ.ORS.STU)6( + 2 253E F"iik1 'A OOE""',<( [string] Wrap a sequence of text chunks and return a list of lines of length 'self.width' or less. (If 'break_long_words' is false, some lines may be longer than this.) Chunks correspond roughly to words and the whitespace between them: each chunk is indivisible (modulo 'break_long_words'), but a line break can come between any two chunks. 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